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- W825133650 abstract "In this work a study of the methods for speech noise reduction based on wavelets is done and, through this study, a new non-thresholding method for speech noise reduction in the wavelet domain is proposed. Generally, a speech signal may be corrupted by artificial or real noise. Let a clean signal be corrupted by white or colored noise, rising a noisy signal in time domain. This work proposes the wavelet application to which gives rise to in the wavelet domain. In this domain, noise is reduced or attenuated without a threshold use. After, the signal is recomposed using the inverse discrete wavelet transform. The most used methods in the wavelet domain wavelet are the thresholding reduction methods, because they allow good results for signals corrupted by white noise, but they do not have the same efficiency when processing signals corrupted by colored noise, this is the most common noise in real situations. In those methods, the threshold is usually calculated in the silence intervals and applied to the whole signal. The coefficients in the wavelet domain are compared with this threshold and those that have absolute value below this value are eliminated or reduced, making a linear application of this threshold. This elimination causes discontinuities in time and in the frequency of the processed signal. Besides, the form with that the threshold is applied can degrade the voice segments of the processed signal, principally in cases that the threshold depends strongly on the last window of the last silence segment. The method proposed in this research consists in the execution of three processing, acting according to their characteristics in the voice and silence segments, without the threshold use. The three processing execution is synthesized in an unique function, called transfer function, acting as a filter in the signal processing. This method has as main objective the overcoming of the deficiencies of the thresholding methods and the effective processing of real noises. When acting, this method is more uniform and introduces less distortion in the processed signal. For the reduction of the noise a reduction curve is generated. This curve is dependent of the signal coefficients, avoiding a differentiated treatment for different segments of the signal. After generating this curve, the reduction is made by the multiplication between the signal coefficients and the curve coefficients. The proposed method is tested in for speech signals, corrupted by white or colored noise. In order to verify the processed signals quality, noise reduction and distortion levels are evaluated using SNR and PESQ measures. The results show that the method is efficient, because it makes the noise reduction without introducing distortions and without changing width. The main advantage of the method proposed in this work, in relation to the other methods of noise reduction in the wavelet domain, is the use of a transfer function that does not use threshold to reduce the noise. This function is not discontinuous, so it does not introduce distortions in the voice segments of the signal." @default.
- W825133650 created "2016-06-24" @default.
- W825133650 creator A5026039416 @default.
- W825133650 date "2009-05-29" @default.
- W825133650 modified "2023-09-28" @default.
- W825133650 title "Um método não-limiar para redução de ruído em sinais de voz no domínio wavelet" @default.
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